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Modeling a Dialogue Strategy for Personalized Movie Recommendations
Department of Computer Science, Linköping University, Linköping, Sweden.ORCID iD: 0000-0002-2791-6647
2005 (English)In: Beyond Personalization 2005: A Workshop on the Next Stage of Recommender Systems Research: San Diego, January 9, 2005 / [ed] Mark van Setten, Sean McNee & Joseph Konstan, 2005, p. 77-82Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses conversational interaction in user-adaptive recommender systems. By collecting and analyzing a movie recommendation dialogue corpus, two initiative types that need to be accommodated in a conversational recommender dialogue system are identified. The initiative types are modeled in a dialogue strategy suitable for implementation. The approach is exemplified by the MADFILM movie recommender dialogue system.

Place, publisher, year, edition, pages
2005. p. 77-82
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-22285OAI: oai:DiVA.org:hh-22285DiVA: diva2:622780
Conference
Intelligent User Interfaces (IUI'05), Beyond Personalization '05 Workshop, San Diego, CA, USA, January 9, 2005
Available from: 2013-05-23 Created: 2013-05-23 Last updated: 2015-05-19Bibliographically approved

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Wärnestål, Pontus

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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  • de-DE
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  • html
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